Link-layer fairness models that have been proposed for wireline and packet cellular networks cannot be generalized for shared channel wireless networks because of the unique characteristics of the wireless channel, such as location-dependent contention, inherent conflict between optimizing channel utilization and achieving fairness, and the absence of any centralized control.In this paper, we propose a general analytical framework that captures the unique characteristics of shared wireless channels and allows the modeling of a large class of systemwide fairness models via the specification of per-flow utility functions. We show that system-wide fairness can be achieved without explicit global coordination so long as each node executes a contention resolution algorithm that is designed to optimize its local utility function.We present a general mechanism for translating a given fairness model in our framework into a corresponding contention resolution algorithm. Using this translation, we derive the backoff algorithm for achieving proportional fairness in wireless shared channels, and compare the fairness properties of this algorithm with both the ideal proportional fairness objective, and state-of-the-art backoff-based contention resolution algorithms.We believe that the two aspects of the proposed framework, i.e. the ability to specify arbitrary fairness models via local utility functions, and the ability to automatically generate local contention resolution mechanisms in response to a given utility function, together provide the path for achieving flexible service differentiation in future shared channel wireless networks.
RFID tags are being used in many diverse applications in increasingly large numbers. These capabilities of these tags span from very dumb passive tags to smart active tags, with the cost of these tags correspondingly ranging from a few pennies to many dollars. One of the common problems that arise in any RFID deployment is the problem of quick estimation of the number of tags in the field up to a desired level of accuracy. Prior work in this area has focused on the identification of tags, which needs more time, and is unsuitable for many situations, especially where the tag set is dense. We take a different, more practical approach, and provide very fast and reliable estimation mechanisms. In particular, we analyze our estimation schemes and show that the time needed to estimate the number of tags in the system for a given accuracy is much better than schemes presented in related work. We show that one can estimate the cardinality of tag-sets of any size in near-constant time, for a given accuracy of estimation.
This paper considers the problem of determining the achievable rates in multi-hop wireless networks. We consider the problem of jointly routing the flows and scheduling transmissions to achieve a given rate vector. We develop tight necessary and sufficient conditions for the achievability of the rate vector. We develop efficient and easy to implement Fully Polynomial Time Approximation Schemes for solving the routing problem. The scheduling problem is a solved as a graph edge-coloring problem. We show that this approach guarantees that the solution obtained is within 67% of the optimal solution in the worst case and, in practice, is typically within about 80 % of the optimal solution. The approach that we use is quite flexible and is a promising method to handle more sophisticated interference conditions, multiple channels, multiple antennas, and routing with diversity requirements.
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